AI Product Manager & Research Lead (26-00255) -

HYBRID

2-3 DAYS ONSITE

POSITION OVERVIEW

This role drives the product strategy, experimentation, and scaling of next-generation AI and Machine Learning solutions within the Financial Services and Insurance business domain. The position bridges high-level commercial objectives with hands-on applied AI research to deliver high-impact, domain-specific AI products.

DAY-TO-DAY RESPONSIBILITIES

• Define and execute the AI product vision, strategy, and research roadmap aligned with business objectives and commercial opportunities.
• Lead cross-functional teams of AI researchers, data scientists, and engineers to design, build, and scale AI-powered products from concept through market adoption.
• Drive applied AI research across Large Language Models (LLMs), agentic AI, embeddings, synthetic data, predictive analytics, and domain-specific ML models.
• Translate complex business challenges into data-driven AI solutions by identifying high-value use cases and setting success metrics.
• Partner with customers, executives, and industry stakeholders to validate product-market fit and communicate technical innovations.
• Establish frameworks for AI experimentation, model evaluation, continuous product improvement, and responsible AI governance.

REQUIRED SKILLS

• 2–3+ years of experience in AI Product Management and AI/ML research execution.
• Hands-on experience with applied AI techniques including LLMs, agentic AI, embeddings, synthetic data, and predictive analytics.
• Proven track record of translating complex domain requirements into scalable data science and ML products.

ADDITIONAL DESIRED SKILLS

• Prior experience in the Insurance or Financial Services industry.
• Deep knowledge of domain-specific machine learning applications and data governance.
• Strong cross-functional leadership and executive presentation skills.

CANDIDATE PROFILE

The ideal candidate is an innovative AI Product Leader and Applied Researcher with strong domain intuition, capable of leading technical teams while driving business adoption. They possess deep analytical rigor paired with a strategic product mindset to turn cutting-edge ML models into commercial enterprise solutions.

Job Responsibilities

• Lead end-to-end development and scaling of AI-powered enterprise products.
• Direct applied research in LLMs, synthetic data, embeddings, and predictive machine learning.
• Partner with technical and business stakeholders to turn complex challenges into actionable AI roadmaps.
• Establish product governance, model testing, and evaluation frameworks.